22 citations · 34 across the 8 of their papers we have counts for
8 papers
Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19
Davide Pigoli, Kieran Baker, Jobie Budd +19
Since early in the coronavirus disease 2019 (COVID-19) pandemic, there has been interest in using artificial intelligence methods to predict COVID-19 infection status based on voca…
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
Harry Coppock, George Nicholson, Ivan Kiskin +22
Recent work has reported that AI classifiers trained on audio recordings can accurately predict severe acute respiratory syndrome coronavirus 2 (SARSCoV2) infection status. Here, w…
A large-scale and PCR-referenced vocal audio dataset for COVID-19
Jobie Budd, Kieran Baker, Emma Karoune +23
The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation of machine learning models that classify SARS-CoV-2 infection status or associated respiratory sympt…
Optimal response surface designs in the presence of model contamination
Olga Egorova, Steven G. Gilmour
Complete reliance on the fitted model in response surface experiments is risky and relaxing this assumption, whether out of necessity or intentionally, requires an experimenter to…
Designs with complex blocking structures and network effects for agricultural field experiments
Vasiliki Koutra, Steven G. Gilmour, Ben M. Parker +1
We propose a novel model-based approach for constructing optimal designs with complex blocking structures and network effects, for application in agricultural field experiments. Th…
Prediction properties of optimum response surface designs
Heloisa M. de Oliveira, Cesar B. A. de Oliveira, Steven G. Gilmour +1
Prediction capability is considered an important issue in response surface methodology. Following the line of argument that a design should have several desirable properties we hav…
Optimal Design of Experiments for Nonlinear Response Surface Models
Yuanzhi Huang, Steven Gilmour, Kalliopi Mylona +1
Many chemical and biological experiments involve multiple treatment factors and often it is convenient to fit a nonlinear model in these factors. This nonlinear model can be mechan…
A graph-theoretic framework for algorithmic design of experiments
Ben M. Parker, Steven G Gilmour, Vasiliki Koutra
In this paper, we demonstrate that considering experiments in a graph-theoretic manner allows us to exploit automorphisms of the graph to reduce the number of evaluations of candid…